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Record W2243824955 · doi:10.54656/cgnr5551

Citizen Science and Youth Audiences: Educational Outcomes of the Monarch Larva Monitoring Project

2008· article· en· W2243824955 on OpenAlexaboutno aff
Dina L. Kountoupes, Karen S. Oberhauser

Bibliographic record

VenueJournal of Community Engagement and Scholarship · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsCitizen sciencePublic relationsPolitical scienceMedical educationSociologyPedagogyMedicine

Abstract

fetched live from OpenAlex

Citizen science projects in which members of the public participate in large scale science research programs are excellent ways for universities to engage the broader community in authentic science research. The Monarch Larva Monitoring Project (MLMP) is such a project. It involves hundreds of individuals throughout the United States and southern Canada in a study of monarch butterfly distribution and abundance. This program, run by faculty, graduate students, and staff at the University of Minnesota, provides research opportunities for volunteer monitors. We used mixed methods to understand contexts, outcomes, and promising practices for engaging youth in this project. Slightly over a third of our adult volunteers engaged youth in monitoring activities. They reported that the youth were successful at and enjoyed project activities, with the exception of data entry. Adults innovations increased the success and educational value of the project for children without compromising data integrity. Many adults engaged in extension activities, including independent research that built on their monitoring observations. This project provides an excellent forum for science and environmental education through investigation, direct and long-term interactions with natural settings, and data analysis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.235
GPT teacher head0.340
Teacher spread0.105 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations59
Published2008
Admission routes1
Has abstractyes

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